DataWords: Getting Contrarian with Text, Structured Data and Explanations

11/09/2021
by   Stephen I. Gallant, et al.
0

Our goal is to build classification models using a combination of free-text and structured data. To do this, we represent structured data by text sentences, DataWords, so that similar data items are mapped into the same sentence. This permits modeling a mixture of text and structured data by using only text-modeling algorithms. Several examples illustrate that it is possible to improve text classification performance by first running extraction tools (named entity recognition), then converting the output to DataWords, and adding the DataWords to the original text – before model building and classification. This approach also allows us to produce explanations for inferences in terms of both free text and structured data.

READ FULL TEXT

page 7

page 8

research
08/15/2022

Syntax-driven Data Augmentation for Named Entity Recognition

In low resource settings, data augmentation strategies are commonly leve...
research
12/20/2019

TreyNet: A Neural Model for Text Localization, Transcription and Named Entity Recognition in Full Pages

In the last years, the consolidation of deep neural network architecture...
research
09/09/2021

SPECTRA: Sparse Structured Text Rationalization

Selective rationalization aims to produce decisions along with rationale...
research
11/10/2021

Improving Structured Text Recognition with Regular Expression Biasing

We study the problem of recognizing structured text, i.e. text that foll...
research
01/15/2013

Factorized Topic Models

In this paper we present a modification to a latent topic model, which m...
research
01/28/2023

How learners produce data from text in classifying clickbait

Text provides a compelling example of unstructured data that can be used...
research
10/24/2020

Measuring Association Between Labels and Free-Text Rationales

Interpretable NLP has taking increasing interest in ensuring that explan...

Please sign up or login with your details

Forgot password? Click here to reset